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Open Graph Description: Contribute to albertleers/Machine-Learning development by creating an account on GitHub.

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https://github.com/albertleers/Machine-Learning#机器学习machine-learning
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前言https://github.com/albertleers/Machine-Learning#preparation
课程列表https://github.com/albertleers/Machine-Learning#curriculum
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推荐书籍列表https://github.com/albertleers/Machine-Learning#booklists
机器学习专项领域学习https://github.com/albertleers/Machine-Learning#special_learning
致谢https://github.com/albertleers/Machine-Learning#many_thanks
https://github.com/albertleers/Machine-Learning#前言
https://github.com/albertleers/Machine-Learning#课程列表
单变量微积分http://open.163.com/movie/2006/8/M/L/M6GLI5A07_M6GLJH1ML.html
Calculus with Analytic Geometryhttps://www.amazon.com/exec/obidos/ASIN/0070576424/ref=nosim/mitopencourse-20
链接https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/
多变量微积分http://open.163.com/special/opencourse/multivariable.html
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线性代数http://open.163.com/special/opencourse/daishu.html
Introduction to Linear Algebrahttp://math.mit.edu/~gs/linearalgebra/
链接https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/study-materials/
统计入门http://open.163.com/movie/2011/6/6/0/M82IC6GQU_M83J9IK60.html
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概率与统计https://www.youtube.com/watch?v=j9WZyLZCBzs&list=PLQ3khvAsNhargDx0dG1cQXOrA2u3JsFKc
Introduction to Probabilityhttps://www.amazon.com/exec/obidos/ASIN/188652923X/ref=nosim/mitopencourse-20
链接https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/tutorials/
矩阵论https://www.amazon.cn/%E7%9F%A9%E9%98%B5%E8%AE%BA-%E6%88%B4%E5%8D%8E/dp/B00116BRO0/ref=sr_1_1?s=books&ie=UTF8&qid=1478614198&sr=1-1&keywords=%E6%88%B4%E5%8D%8E%EF%BC%8C+%E7%9F%A9%E9%98%B5%E8%AE%BA
凸优化1https://lagunita.stanford.edu/courses/Engineering/CVX101/Winter2014/about
Convex Optimizationhttp://www.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf
链接http://stanford.edu/class/ee364a/index.html
凸优化2https://www.youtube.com/watch?v=U3lJAObbMFI&list=PL3940DD956CDF0622&index=20
链接http://stanford.edu/class/ee364b/
统计学习入门https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
An Introduction to Statistical Learninghttp://www-bcf.usc.edu/~gareth/ISL/
链接https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
机器学习基石https://www.coursera.org/instructor/htlin
Learning from Datahttps://www.amazon.com/gp/product/1600490069
链接https://www.csie.ntu.edu.tw/~htlin/course/mlfound16fall/
机器学习技法https://www.coursera.org/instructor/htlin
链接https://www.csie.ntu.edu.tw/~htlin/course/ml15fall/
机器学习https://www.youtube.com/watch?v=mbyG85GZ0PI&index=1&list=PLD63A284B7615313A
Learning from Datahttps://www.amazon.com/gp/product/1600490069
链接http://work.caltech.edu/lectures.html
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链接http://cs229.stanford.edu/materials.html
https://github.com/albertleers/Machine-Learning#推荐学习路线
https://github.com/albertleers/Machine-Learning#数学基础初级
单变量微积分http://open.163.com/movie/2006/8/M/L/M6GLI5A07_M6GLJH1ML.html
Calculus with Analytic Geometryhttps://www.amazon.com/exec/obidos/ASIN/0070576424/ref=nosim/mitopencourse-20
链接https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/
多变量微积分http://open.163.com/special/opencourse/multivariable.html
Multivariable Calculushttps://www.amazon.com/exec/obidos/ASIN/0130339679/ref=nosim/mitopencourse-20
链接https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/
线性代数http://open.163.com/special/opencourse/daishu.html
Introduction to Linear Algebrahttp://math.mit.edu/~gs/linearalgebra/
链接https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/study-materials/
统计入门http://open.163.com/movie/2011/6/6/0/M82IC6GQU_M83J9IK60.html
链接1http://mooc.guokr.com/course/461/%E6%A9%9F%E7%8E%87/
链接2https://www.youtube.com/watch?v=GwSEguqJj6U&index=1&list=PLtvno3VRDR_jMAJcNY1n4pnP5kXtPOmVk
概率与统计https://www.youtube.com/watch?v=j9WZyLZCBzs&list=PLQ3khvAsNhargDx0dG1cQXOrA2u3JsFKc
Introduction to Probabilityhttps://www.amazon.com/exec/obidos/ASIN/188652923X/ref=nosim/mitopencourse-20
链接https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/tutorials/
https://github.com/albertleers/Machine-Learning#程序语言能力
链接http://cs231n.github.io/python-numpy-tutorial/
https://github.com/albertleers/Machine-Learning#机器学习课程初级
统计学习入门https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
An Introduction to Statistical Learninghttp://www-bcf.usc.edu/~gareth/ISL/
链接https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
机器学习入门https://www.coursera.org/learn/machine-learning
链接https://www.coursera.org/learn/machine-learning
https://github.com/albertleers/Machine-Learning#数学基础中级
矩阵论https://www.amazon.cn/%E7%9F%A9%E9%98%B5%E8%AE%BA-%E6%88%B4%E5%8D%8E/dp/B00116BRO0/ref=sr_1_1?s=books&ie=UTF8&qid=1478614198&sr=1-1&keywords=%E6%88%B4%E5%8D%8E%EF%BC%8C+%E7%9F%A9%E9%98%B5%E8%AE%BA
凸优化1https://lagunita.stanford.edu/courses/Engineering/CVX101/Winter2014/about
Convex Optimizationhttp://www.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf
链接http://stanford.edu/class/ee364a/index.html
凸优化2https://www.youtube.com/watch?v=U3lJAObbMFI&list=PL3940DD956CDF0622&index=20
链接http://stanford.edu/class/ee364b/
Convex Optimization: Algorithms and Complexityhttps://link.zhihu.com/?target=http%3A//arxiv.org/abs/1405.4980
https://github.com/albertleers/Machine-Learning#机器学习课程中级
机器学习基石https://www.coursera.org/instructor/htlin
Learning from Datahttps://www.amazon.com/gp/product/1600490069
链接https://www.csie.ntu.edu.tw/~htlin/course/mlfound16fall/
机器学习技法https://www.coursera.org/instructor/htlin
链接https://www.csie.ntu.edu.tw/~htlin/course/ml15fall/
机器学习http://open.163.com/movie/2008/1/M/C/M6SGF6VB4_M6SGHFBMC.html
链接http://cs229.stanford.edu/materials.html
机器学习https://www.youtube.com/watch?v=mbyG85GZ0PI&index=1&list=PLD63A284B7615313A
Learning from Datahttps://www.amazon.com/gp/product/1600490069
链接http://work.caltech.edu/lectures.html
https://github.com/albertleers/Machine-Learning#推荐书籍列表
统计学习方法https://www.amazon.cn/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95-%E6%9D%8E%E8%88%AA/dp/B007TSFMTA
An Introduction to Statistical Learninghttp://www-bcf.usc.edu/~gareth/ISL/
Machine Learninghttps://www.amazon.com/gp/product/0071154671?ie=UTF8&tag=jefork-20&linkCode=as2&camp=1789&creative=9325&creativeASIN=0071154671
Learning from Datahttps://www.amazon.com/gp/product/1600490069
配套讲义https://work.caltech.edu/telecourse.html
Pattern Recognition and Machine Learninghttps://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738/ref=pd_sim_14_1?ie=UTF8&dpID=61f0EXfMRvL&dpSrc=sims&preST=_AC_UL160_SR118%2C160_&refRID=119X50P5F0DFA339S9DR
配套讲义http://cs.brown.edu/courses/csci1420/lectures.html
The Elements of Statistical Learninghttps://www.amazon.com/The-Elements-Statistical-Learning-Prediction/dp/0387848576/ref=pd_sim_14_2?ie=UTF8&dpID=41LeU3HcBdL&dpSrc=sims&preST=_AC_UL160_SR103%2C160_&refRID=119X50P5F0DFA339S9DR
Understanding Machine Learning:From Theory to Algorithmshttp://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf
Machine Learning: A probabilistic approachhttps://www.amazon.com/Machine-Learning-Probabilistic-Perspective-Computation/dp/0262018020
https://github.com/albertleers/Machine-Learning#机器学习专项领域学习
https://github.com/albertleers/Machine-Learning#一些专项领域资料
深度学习https://github.com/JustFollowUs/Deep-Learning
图模型https://github.com/JustFollowUs/Probabilistic-graphical-models
强化学习https://github.com/JustFollowUs/Reinforcement-Learning
Hashhttp://cs.nju.edu.cn/lwj/L2H.html
理论机器学习https://github.com/JustFollowUs/Theoretical-Machine-Learning/
https://github.com/albertleers/Machine-Learning#领域会议期刊
NIPShttps://nips.cc/
ICMLhttp://icml.cc/
AAAIhttp://www.aaai.org/
IJCAIhttp://www.ijcai.org/
KDDhttp://www.kdd.org/
ICDMhttp://www.cs.uvm.edu/~icdm/
COLThttp://www.learningtheory.org/
https://github.com/albertleers/Machine-Learning#致谢
Readme https://github.com/albertleers/Machine-Learning#readme-ov-file
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Communityhttps://github.community/
Docshttps://docs.github.com/
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